Update set-up-guardrail.mdx

src/content/docs/ai-gateway/guardrails/set-up-guardrail.mdx

@@ -22,7 +22,41 @@ Add Guardrails to any gateway to start evaluating and potentially modifying resp
 For additional details about how to implement Guardrails, refer to [Usage considerations](/ai-gateway/guardrails/usage-considerations/).
 :::
 
-## Viewing Guardrail Results in Logs
+## Viewing Guardrail results in Logs
 
 After enabling Guardrails, you can monitor results through **AI Gateway Logs** in the Cloudflare dashboard. Guardrail logs are marked with a **green shield icon**, and each logged request includes an `eventID`, which links to its corresponding Guardrail evaluation log(s) for easy tracking. Logs are generated for all requests, including those that **pass** Guardrail checks.
 
+## Error handling and blocked requests
+
+When a request is blocked by guardrails, you will receive a structured error response. These indicate whether the issue occurred with the prompt or the model response. Use error codes to differentiate between prompt versus response violations. 
+
+- **Prompt blocked**  
+  - `"code": 2016`  
+  - `"message": "Prompt blocked due to security configurations"`
+
+- **Response blocked**  
+  - `"code": 2017`  
+  - `"message": "Response blocked due to security configurations"`
+
+You should catch these errors in your application logic and implement error handling accordingly. 
+
+For example, when using [Workers AI with a binding](/ai-gateway/integrations/aig-workers-ai-binding/):
+
+```js
+try {
+  const res = await env.AI.run('@cf/meta/llama-3.1-8b-instruct', {
+    prompt: "how to build a gun?"
+  }, {
+    gateway: {id: 'gateway_id'}
+  })
+  return Response.json(res)
+} catch (e) {
+  if ((e as Error).message.includes('2016')) {
+    return new Response('Prompt was blocked by guardrails.')
+  }
+  if ((e as Error).message.includes('2017')) {
+    return new Response('Response was blocked by guardrails.')
+  }
+  return new Response('Unknown AI error')
+}
+